Download Translation

Bacterial infection by lytic virus
Replication
Transcription
Translation
Central Dogma of Molecular Biology
replication
DNA
transcription
RNA
translation
Protein
Phage genes are replicated/transcribed/translated by bacterial machinery
Replication – DNA Polymerase
Transcription- RNA polymerase
Translation- Ribosome
“Central Dogma of Molecular Biology”
Flow of information from DNA  RNA  Protein
Schematic image of gene structure
ATG
GTG
TTG
TAG
TGA
TAA
ATG
GTG
TTG
TAG
TGA
TAA
Shine Dalgarno box = Ribosome binding site
Signal sequence in prokaryotic mRNA
~4-14 bp upstream from start codon
Ribosome binding site to initiate translation
16s rRNA is part of 30S subunit
**You will look for a “SD score” as one
measure of a good start codon prediction.
Translation
ribosome
anticodon
codon
tRNA
The genetic code:
-Is read by the ribosome, converting RNA into proteins
-Is redundant, or degenerate (there are 64 codons, and only 20 amino acids)
-Is the same in almost all organisms
Translation in individual organisms may be biased towards particular tRNA
pool, GC content, etc.
The Ribosome recognizes the correct reading frame
Silly example:
the mad cat ate the fat rat and the big bat
t hem adc ata tet hef atr ata ndt heb igb at
th ema dca tat eth efa tra tan dth ebi gba t
Science example:
ATGAATATGAAAACAACTATTAAAGCAGGTCAATTCGAATTAGGACAAGTG
Coding Potential
Organisms have a preference for certain codons.
Six frame translation
This document shows the six potential reading frames, with each predicted gene highlighted.
protein1
protein2
Frame 1
Frame 2
Frame 3
Frame 4
Frame 5
Frame 6
Coding Potential
Organisms have a preference for certain codons.
This plot shows predicted open reading frames based on ‘coding potential’.
Frame 1
Frame 2
Frame 3
What does coding potential tell you?
Upticks are start codons
Downticks are stop codons
Predicts open reading frames (thick black bar) based on how well the codon usage matches
1) The host bacteria (black line)
2) The phage (red line)
BLAST: Basic Local Alignment Search Tool
•
•
•
•
The most highly used bioinformatics tool?
Finds similarity between biological sequences (DNA or Protein)
Compares your favorite protein to the “non-redundant” database
Shows alignment and calculates statistical significance
BLASTn uses nucleotide input and compares to a nucleotide sequence database
BLASTp uses amino acid input and compares to a proteni sequence database
Evaluating a BLASTp match
Query- your protein sequence
Subject- the match from the database
Look through alignment, what kinds of scores are represented?
Look through text list of hits, how does your Query coverage and E value look?
How does % identity look?
Do the words describing the hits tell you anything?
Look at the first few alignments:
Query and Subject are aligned.
Identical amino acids are shown by the same letter being in the middle of
the two sequences.
+ means the amino acids are similar. A blank means they are different.
– means the computer put in a ‘gap’ (not real) so it could make the best
alignment possible.
***Do you get a 1:1 match of query:subject?
Ribosomes recognize the Shine-Dalgarno sequence
“AGGAGG” core
4-14 nucleotides upstream of start
DNA Frames view gives you the “SD score”
Work through the annotation of gp1 using the guiding principles of annotation
Start/stop coordinates
Enter after you make your choice
Length
In features table or description tab
Longest ORF?
Yes, or no but…
Gap/overlap to previous
gene
Can ignore for gp1, remember gaps -1, overlaps +1
Predicted by
Genemark or Glimmer or Self
SD Score
In frames view, is it the highest?
Coding potential
In GeneMark files on wiki
Best BLASTp match
Is it 1:1 and for most of the query length?
Function
Based on homology or ‘Hypothetical Protein’
Function source
Blastp conserved domain, Phamerator, hhpred
Homework: Annotate the first three genes!
-post your annotations on your wiki page
**every semester one or two students lose
their annotations
-be sure to save your DNAMaster file on
your computer in Documents and
somewhere else (USB or wiki)